Pune: ManageEngine, the enterprise IT management division of Zoho Corporation, is witnessing strong growth momentum in India, positioning the country among its top global markets, according to Aparna TA, Head of Enterprise IT Solutions at ManageEngine.
With India emerging as a technology-first economy and a major contributor to global IT services, ManageEngine sees the market as strategically critical for both product adoption and long-term innovation.
Aparna TA noted that India’s deep technology talent pool and mature IT services ecosystem make it a natural fit for ManageEngine’s enterprise-focused products.
These solutions are already widely used by Indian companies to deliver services to their global customers.
As a result, India is rapidly becoming ManageEngine’s second or third largest market worldwide, reflecting sustained investments made by the company over the past few years.
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ManageEngine Highlights Pune’s Role as a GCC and Innovation Hub
According to ManageEngine, Pune is playing a pivotal role in its India strategy as the city evolves into a prominent global capability centre (GCC) hub.
The availability of skilled talent, a robust technology ecosystem, and a mature human resource marketplace make Pune a strategic location compared to many global alternatives, says Aparna.
She emphasised that ManageEngine’s focus remains closer to customer-facing enterprise technologies rather than purely foundational systems, aligning well with the city’s strengths.
ManageEngine’s AI Strategy Focuses on Full-Stack Ownership
Addressing the role of artificial intelligence, Aparna TA outlined a clear distinction between using AI to run its internal operations and deploying AI to create customer value.
The company’s AI strategy is anchored in long-term thinking and full-stack ownership, enabled through Zoho Labs, its shared research and development facility.
ManageEngine operates its AI models on infrastructure it owns and manages, including GPUs, reducing dependence on external cloud providers and avoiding premium costs.
The company leverages open-source AI models, enhances them using deep domain expertise built over more than two decades, and deploys them contextually within enterprise workflows to ensure practical, real-world value.
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ManageEngine Emphasises Sustainable AI Over Rapid Deployment
Rather than adopting AI as a short-term trend, ManageEngine is building its AI capabilities from the ground up, with a focus on compounding intellectual capital over five to ten years.
The company believes that while speed and rapid deployment are important, sustainable value creation requires deep knowledge, controlled infrastructure, and responsible design.
Aparna TA also highlighted the risks of over-reliance on capital-intensive AI models that may become unsustainable over time.
Its approach is designed to ensure continuity for customers, even as AI systems evolve, by embedding intelligence deeply into enterprise workflows rather than offering standalone or experimental solutions.
ManageEngine Offers Flexible Cloud and Hybrid Deployment Models
This flexibility addresses the growing complexity of cloud management and supports organizations operating in hybrid IT environments that combine legacy on-premises systems with modern cloud infrastructure.
ManageEngine Applies AI Thoughtfully to Enterprise Cybersecurity
Cybersecurity remains a major focus area for ManageEngine, particularly as enterprise environments become more distributed and cloud-driven.
Aparna TA highlighted that modern organizations often lack visibility into the tools, applications, and data being used across their environments, fundamentally changing the security landscape.
Aparna explained that while enterprises now deploy multiple security tools to gain visibility, this often results in thousands of alerts per day – far beyond what human teams can realistically handle.
AI plays a critical role in processing large volumes of security data, identifying known patterns, detecting anomalies, and clustering alerts to improve operational efficiency.
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ManageEngine Balances AI Automation With Human Oversight
While AI excels at handling repetitive and data-intensive tasks, ManageEngine stressed that human judgment remains essential in scenarios involving intent, business context, and accountability.
For example, unusual access patterns may be flagged by AI, but human oversight is required to determine whether the activity is legitimate.
Legal compliance, governance, and final decision-making continue to rest with human teams. As a result, ManageEngine designs its cybersecurity solutions to strike a balance between automation and human involvement, ensuring responsible and practical AI adoption.
ManageEngine Showcases AI-Driven Endpoint and Security Operations Efficiency
ManageEngine shared examples of how large enterprises use a combination of AI and human expertise to improve security operations.
In organizations with tens of thousands of employees and devices, endpoints represent a primary attack surface.
ManageEngine’s unified endpoint management and security solutions use AI-driven pattern recognition to detect malware, isolate compromised devices, and prevent lateral movement across networks.
AI is also used to analyse VPN usage, detect unusual login behaviour, and trigger alerts when access patterns deviate from established norms.
These capabilities are supported by employee awareness and training, reinforcing a layered security approach, said Aparna.
Measuring AI Impact Through Operational Efficiency
Rather than assigning direct monetary values, Aparna says that ManageEngine measures AI impact through operational metrics such as reduced alert volumes, automated incident resolution, and improved response times.
AI systems summarise and cluster alerts into concise insights, enabling security teams to focus on high-priority incidents.
The company’s AI models operate in two layers: a base intelligence layer and a customer-specific learning layer that adapts to individual environments.
Importantly, insights from one customer are not transferred to another, ensuring data isolation and responsible AI behaviour, she said.
